The Internet shutdown muzzle(s) freedom of expression in Ethiopia: competing narratives

Freedom of expression is a foundational stone for democracy and embraces a number of other rights, including – freedom to seek, receive, and impart information using any medium. Around 16 million Ethiopians, comprising 15.4% of the total population, use the Internet. The Ethiopian Internet shutdown saga has been marked by competing narratives. On one hand, the government has been using two governing narratives, i.e. national security narrative and ‘economic growth’ narrative to justify shutdowns of the Internet. But, the individuals’ self-expressions on social media find itself as competing narrative. Since 2016, the Internet has been closed more than six times under the cloak of national security, quelling rising protests, controlling strikes, and exam cheating. As such, freedom of expression of millions has been muzzled. The article argues blanket Internet shutdowns do not meet the caveats of human rights law.     

Alcohol Determination in Distilled Alcoholic Beverages by Liquid Phase Fourier Transform Mid-Infrared and Near-Infrared Spectrophotometries

Fourier transform mid-infrared spectrophotometry (FT-MIR), 1180–950 cm^?1, and near-infrared spectrophotometry (NIR), 1720–1660 nm, have been used complementarily for the direct determination of ethanol and methanol in distilled alcoholic beverages. In mid-infrared ethanol and methanol identified separately, hence, it has been used to confirm the absence or presence of methanol. In the absence of methanol, both were used to determine the alcoholic strength independently; however, near-infrared was used without diluting the samples. Ethanol and methanol contents were evaluated using the calibration curves established by a plot of peak height or peak area versus concentration % (w/w). The linearity range for ethanol was up to 15 and 50 % (w/w) for mid- and near-infrared, respectively. The developed methods are simple, fast, precise, and accurate. Moreover, the results obtained were in excellent agreement with the results obtained from gas chromatographic measurements. No sample preparation was required at all, and in all samples, methanol was not detected.     

The effect of increased interrogation zone,reader antenna polarization and application factors in the performance of UHF RFID tag detection on modified atmosphere packaged meat

The effect of conveyor speed, test sample size, antenna to sample distance, antenna polarization and ideal tag location in relation to the coupling capabilities of ultra‐high frequency radio frequency identification on optimal reader antenna placement were studied. The influence of each individual factor and its interaction was determined using the general linear model analysis of variance. In decreasing order of significance of the variables tested were sample type (F = 4174.40, p < 0.0005), smaller samples preferred for coupling; distance (F = 863.83, p < 0.0005), where distance between sample and antenna should be kept to a minimum; inlay design (F = 167.82, p < 0.0005), where AD‐612 preformed best due to its large antenna area; and reader antenna polarization (F = 149.64, p < 0.0005), where circular polarization preformed better yet comparative advantage decreased with distance. A reader antenna offset of 95 mm, while not significant, (F = 1.73, p = 0.188) tended to decrease coupling capabilities of the system despite increasing the zone of influence. Ideal tag location on sample was found to be on the right, back and front face with y‐orientation proving superior than either x or z. A 190‐mm centre–to‐centre reader antenna offset resulted in a decrease in the average tag detection rate from 62 to 49% highlighting the importance of optimal reader antenna placement which needs to be confirmed if a similar result is to be obtained when a large number of tags are interrogated simultaneously. Copyright © 2010 John Wiley & Sons, Ltd.     

The effects of item composition,tag inlay design,reader antenna polarization,power and transponder orientation on the dynamic coupling efficiency of backscatter ultra‐high frequency radio frequency identification

The effects of packaged content, packaging material, transponder inlay design, reader antenna polarization, interrogation power and transponder orientation on the detection rate of ultra‐high frequency radio frequency identification (UHF RFID) passive transponders were studied. The influence of individual factors and their interactions were determined using general linear model analysis of variance. Influences originated in order of importance, from sample type, antenna polarization, power and inlay design. Important interactions in decreasing order of significance exist between: power and antenna polarization; sample type and antenna polarization; sample type and inlay design; inlay design and antenna polarization; sample type, power and antenna polarization; sample type and power; inlay design and power; sample type, inlay design and power. It was also observed that random orientation of tags did not cause a statistically significant variation in tag detection rate. It can be concluded that the use of UHF RFID for item level of food requires multi‐parameter assessment before hand. Copyright © 2009 John Wiley & Sons, Ltd.     

Deregulation as a switch of regime: Price effects using a modified Hotelling rule

Concern over rising energy prices has led to support for government intervention to regulate the price of domestic non-renewable energy resources. However, US policy makers appear to be looking more towards competition, rather than regulation, to decide who will provide energy resources and how these will be priced. This paper models possible dynamic price effects occasioned by the removal of a regulatory constraint. The analysis focuses on a government decision to eliminate binding price ceilings on a non-renewable (energy) substitute when the incumbent resource is monopolistically controlled (using deregulation of natural gas as an illustration). Under certain conditions it is shown that one will get continuity of marginal revenue and a fall in the world price following decontrol (the expiration of a patent or a decision to grant mineral rights on federal land). In general, however, the model suggests that both marginal revenue and prices will be discontinuous and that the discontinuity is likely to result in a fall in price.     

Assessment of the sensory quality and shelf stability of selected Horro beef muscles in Ethiopia

The objective of this work was to assess sensory quality and retail life of Horro beef muscles in Ethiopia. Six muscles: M. rhomboideus (RM), M. infraspinatus (IS), M. longissimus lumborum (LL), M. semimembranosus (SM), M. biceps femoris (BF) and M. rectus femoris (RF) were considered. Sensory quality of the muscles was rated by a 9-member trained panel for palatability, tenderness, juiciness, amount of connective tissue (ACT), lean color and surface discoloration and measured by Warner-Bratzler Shear Force (WBSF). Retail life of the six muscles were evaluated for CIE 1976 L^∗a^∗b^∗ color values across 6 days. Significant differences (p < 0.05) between muscles for all sensory attributes and WBSF were found. Significant L^∗a^∗b^∗ color values of muscles and USDA quality grades by retail life were found (p < 0.05). Significant correlations (p < 0.05 or p < 0.01) of key parameters were also identified.     

An Approach for Integrating Valuable Flexibility During Conceptual Design of Networks

Energy and industrial networks such as pipeline-based carbon capture and storage infrastructures and (bio)gas infrastructures are designed and developed in the presence of major uncertainties. Conventional design methods are based on deterministic forecasts of most likely scenarios and produce networks that are optimal under those scenarios. However, future design requirements and operational environments are uncertain and networks designed based on deterministic forecasts provide sub-optimal performance. This study introduces a method based on the flexible design approach and the concept of real options to deal with uncertainties during conceptual design of networks. The proposed method uses a graph theoretical network model and Monte Carlo simulations to explore candidate designs, and identify and integrate flexibility enablers to pro-actively deal with uncertainties. Applying the method on a hypothetical network, it is found that integrating flexibility enablers (real options) such as redundant capacity and length can help to enhance the long term performance of networks. When compared to deterministic rigid designs, the flexible design enables cost effective expansions as uncertainty unfolds in the future.     

Detection and classification of large bowel obstruction from X-ray images using machine learning algorithms

Large bowel obstruction (LBO) occurs when there is a blockage or twisting in the large bowel that prevents wastes and gas from passing through. If left untreated, the blockage cuts off blood supply to the colon, causing sections of it to die which results in high rates of morbidity and fatality. The examination of clinical symptoms of LBO involves careful inspection of the cecum and colon. Radiologists use X-rays to inspect the clinical signs. Some research has been done to automate the detection of related abdominal and intestinal diseases. However, all these studies concentrate only on detecting Crohn's, ulcerative colitis, Acute Appendicitis, colorectal cancer, celiac diseases, liver diseases, and chronic kidney diseases. Automatic detection and classification of LBO has not been given due attention so far to the best of the authors knowledge. To address this challenge, we have designed a model for the detection and classification of LBO. The models development comprises of stages such as preprocessing, detection, segmentation, feature extraction, and classification. We used YOLOv3 for detection and used a gray scale level co-occurrence matrix (GLCM), and a convolutional neural network for feature extraction, while support vector machine (SVM) and softmax were used for classification. The proposed model achieved a diagnostic accuracy of 89% when feature extraction methods such as CNN and median filter with softmax classifier were used. CNN and Gaussian filter with soft max classifier achieved 91%, while CNN and anisotropic filter with soft max classifier achieved 92%. GLCM with threshold segmentation and Gaussian filter with SVM classifier achieved 87%, while CNN with watershed segmentation and Gaussian filter with SVM classifier achieved 97% and CNN-GLCM with watershed segmentation and anisotropic diffusion filter with SVM classifier achieved 98% for detection and classification of LBO. Finally, this paper presented a performance analysis of various machine learning approaches for detection and classification of LBO. Hence, our model is designed to assist human experts (Radiologists) in diagnosing LBO.